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LIS590DT Data Mining Applications

Description: Data mining refers to the process of exploring large datasets with the goal of uncovering interesting patterns. This process usually involves a number of tasks such as data collection, pre-processing, and characterization; model fitting, selection, and evaluation; classification, clustering, and prediction. Although data mining has its roots in database management, it has grown into a discipline that focuses on algorithm design (to ensure computational feasibility) and statistical modeling (to separate the signal from the noise). As such, it draws heavily upon a variety of other disciplines including statistics, machine learning, operations research, and information retrieval. This course will cover the major data mining concepts, principles, and techniques that *every information scientist should know about.* Lectures will introduce and discuss the major approaches to data mining, computer lab sessions coupled with assignments will provide hands-on experience with these approaches, and term projects offer the opportunity to use data mining in a novel way. Mathematical detail will be left to the students who are so inclined.
Credit Hours: 2 or 4 GR hours
Note: 2 or 4 hours. Be sure to enroll in your desired amount of credit.

Schedule: W: 9:00 - 11:50 a.m.
Location: 52 LISB
Instructor: Torvik

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